We are seeking a Senior Data Scientist to join an Intelligent Solutions Delivery team, supporting the delivery of AI‑enabled solutions for Claims and enterprise transformation initiatives. This role is focused on building, validating, and productionising AI and machine learning solutions that are embedded directly into business workflows, with a strong emphasis on responsible, governed, and scalable AI delivery.
You will work closely with AI Solution Architects, Engineers, Claims SMEs, and Delivery Squads to develop models and intelligent components using Databricks AI/ML frameworks, Python, and SQL, contributing to agent‑based, predictive, and decision‑support solutions across the claims lifecycle.
Key Responsibilities
* Design, build, and iterate machine learning and AI solutions that support Claims transformation initiatives (e.g. triage, summarisation, risk detection, decision support).
* Develop analytical and ML components that can be embedded into agentic and AI‑assisted workflows.
* Apply appropriate modelling techniques (predictive modelling, NLP, classification, regression, anomaly detection) aligned to business outcomes.
* Build and manage models using Databricks AI/ML frameworks, leveraging scalable compute and governed data access.
* Use Python for feature engineering, model training, evaluation, and inference logic.
* Use SQL to extract, transform, and validate data used in AI and ML pipelines.
* Contribute to reusable notebooks, pipelines, and patterns that accelerate AI delivery across squads.
* Support the transition of models from experimentation to production, working with engineers on deployment patterns within Databricks.
* Implement model documentation, performance tracking, and validation artefacts to support model risk, compliance, and audit requirements.
* Monitor model behaviour over time (performance, drift, stability) and recommend improvements.
Skills & Experience (Required)
* Proven experience delivering data science or machine learning solutions in a production or enterprise environment.
* Strong hands‑on experience with Python for data analysis and ML development.
* Experience working with Databricks, including AI/ML workloads and notebook‑based development.
* Solid SQL capability for data exploration, feature creation, and validation.
* Experience across the ML lifecycle: problem framing, data preparation, modelling, evaluation, and operational handover.
* Strong communication skills and ability to work in cross‑functional delivery teams.
* Partner with Intelligent Solutions Delivery squads, Solution Architects, and engineers to ensure AI components align to end‑to‑end solution design.
* Collaborate with Claims, Operations, and Risk stakeholders to validate assumptions and ensure models are interpretable and fit‑for‑purpose.
Desirable Experience
* Exposure to agentic AI, GenAI, NLP, or AI‑assisted workflows.
* Experience working in regulated or risk‑aware environments (e.g. financial services, insurance).
* Familiarity with MLOps practices (model versioning, reproducibility, monitoring).
* Understanding of ethical AI, explainability, and governance considerations.
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